SOTAVerified

Transfer Learning

Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.

( Image credit: Subodh Malgonde )

Papers

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Showing 8426–8450 of 10307 papers

TitleStatusHype
Unsupervised Attention Based Instance Discriminative Learning for Person Re-IdentificationCode0
Transfer of Deep Reactive Policies for MDP PlanningCode0
Transfer and Active Learning for Dissonance Detection: Addressing the Rare-Class ChallengeCode0
Unsupervised Chunking as Syntactic Structure Induction with a Knowledge-Transfer ApproachCode0
Transfer Learning Bayesian Optimization to Design Competitor DNA Molecules for Use in Diagnostic AssaysCode0
Transfer of Pretrained Model Weights Substantially Improves Semi-Supervised Image ClassificationCode0
Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatial-Temporal PatternsCode0
Time and Cost-Efficient Bathymetric Mapping System using Sparse Point Cloud Generation and Automatic Object DetectionCode0
Transfer of Structural Knowledge from Synthetic LanguagesCode0
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression ExtractionCode0
Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controlsCode0
Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial LossCode0
End-to-End Learning on 3D Protein Structure for Interface PredictionCode0
Transfer Learning based Detection of Diabetic Retinopathy from Small DatasetCode0
Unsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case StudyCode0
Thieves on Sesame Street! Model Extraction of BERT-based APIsCode0
Why does Knowledge Distillation Work? Rethink its Attention and Fidelity MechanismCode0
Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative StudyCode0
Transfer Learning of Deep Spatiotemporal Networks to Model Arbitrarily Long Videos of SeizuresCode0
Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundariesCode0
Unsupervised Disentangling of Appearance and Geometry by Deformable Generator NetworkCode0
Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain AdaptationCode0
Transfer Learning-based Channel Estimation in Orthogonal Frequency Division Multiplexing Systems Using Data-nulling Superimposed PilotsCode0
Transfer Learning of CATE with Kernel Ridge RegressionCode0
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer LearningCode0
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified